Correlation Between Formetal and Koryo Credit
Can any of the company-specific risk be diversified away by investing in both Formetal and Koryo Credit at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Formetal and Koryo Credit into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Formetal Co and Koryo Credit Information, you can compare the effects of market volatilities on Formetal and Koryo Credit and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Formetal with a short position of Koryo Credit. Check out your portfolio center. Please also check ongoing floating volatility patterns of Formetal and Koryo Credit.
Diversification Opportunities for Formetal and Koryo Credit
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Formetal and Koryo is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding Formetal Co and Koryo Credit Information in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Koryo Credit Information and Formetal is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Formetal Co are associated (or correlated) with Koryo Credit. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Koryo Credit Information has no effect on the direction of Formetal i.e., Formetal and Koryo Credit go up and down completely randomly.
Pair Corralation between Formetal and Koryo Credit
Assuming the 90 days trading horizon Formetal Co is expected to generate 7.05 times more return on investment than Koryo Credit. However, Formetal is 7.05 times more volatile than Koryo Credit Information. It trades about 0.13 of its potential returns per unit of risk. Koryo Credit Information is currently generating about -0.16 per unit of risk. If you would invest 311,192 in Formetal Co on October 16, 2024 and sell it today you would earn a total of 28,308 from holding Formetal Co or generate 9.1% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Formetal Co vs. Koryo Credit Information
Performance |
| Timeline |
| Formetal |
| Koryo Credit Information |
Formetal and Koryo Credit Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Formetal and Koryo Credit
The main advantage of trading using opposite Formetal and Koryo Credit positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Formetal position performs unexpectedly, Koryo Credit can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Koryo Credit will offset losses from the drop in Koryo Credit's long position.| Formetal vs. SBI Investment KOREA | Formetal vs. DC Media Co | Formetal vs. Nice Information Telecommunication | Formetal vs. NH Investment Securities |
| Koryo Credit vs. Nable Communications | Koryo Credit vs. Digital Power Communications | Koryo Credit vs. Korea Information Communications | Koryo Credit vs. Formetal Co |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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